# Synergized_LLMs_KGs

**Repository Path**: xpnb/Synergized_LLMs_KGs

## Basic Information

- **Project Name**: Synergized_LLMs_KGs
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 5
- **Created**: 2023-11-15
- **Last Updated**: 2023-12-15

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# LLMs+KGs协同论文阅读与汇报



## 阅读计划

### lxp：

- [MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models](https://proceedings.neurips.cc/paper_files/paper/2022/hash/f224f056694bcfe465c5d84579785761-Abstract-Conference.html)
- Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph, ICLR24

### ltq:

- A Unified Knowledge Graph Augmentation Service for Boosting Domain-specific NLP Tasks, Available: https://aclanthology.org/2023.findings-acl.24

- Unifying Structure Reasoning and Language Pre-training for Complex Reasoning Tasks, Available: https://ieeexplore.ieee.org/abstract/document/10288055

### cwq:

- DRGON:Deep Bidirectional Language-Knowledge Graph Pretraining
- JointGT:Ke P, Ji H, Ran Y, et al. Jointgt: Graph-text joint representation learning for text generation from knowledge graphs[J]. arXiv preprint arXiv:2106.10502, 2021.

### fjw:

- Yao L, Mao C, Luo Y. KG-BERT: BERT for Knowledge Graph Completion[A]. arXiv, 2019.
- J. Lovelace and C. P. Ros ́ e, “A framework for adapting pre-trained language models to knowledge graph completion,” in Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022, Abu Dhabi, United Arab Emirates, December 7-11, 2022, Y. Goldberg, Z. Kozareva, and Y. Zhang, Eds. Association for Computational Linguistics, 2022, pp. 5937–5955. [Online]. Available: https: //aclanthology.org/2022.emnlp-main.398